> For the complete documentation index, see [llms.txt](https://docs.alkemi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.alkemi.ai/documentation/basics/data-products/creating-a-data-product.md).

# Creating a Data Product

{% @arcade/embed flowId="rVam69xh9gImvdEBnTa2" url="<https://app.arcade.software/share/rVam69xh9gImvdEBnTa2>" %}

{% stepper %}
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### Select "Data Products" from your account menu

Go to the Data Products management page by choosing **Data Products** from the drop-down menu in the top-right corner of the DataLab interface.

<figure><img src="/files/cNPv89Kf3iH4jKWRlGP9" alt=""><figcaption></figcaption></figure>
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{% step %}

### Begin creating your Data Product

1. Click the **+Data Product** button.
2. Enter your data product details. By default, your data product is internal and only visible within your organization. To make it public, adjust the privacy setting during creation or you can edit it later.
3. Select a Data Provider for your data product. Commonly, this is your organization's name. To add a new provider, go to the Data Providers section.
4. Name your data product and provide a description.

<figure><img src="/files/PiSOSDsuXpJH8SCgO0W7" alt="" width="375"><figcaption></figcaption></figure>
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{% step %}

## Selecting a Data Source and Tables

1. **Connect Your Data Source**: Follow our guides in [Connect your data](/documentation/getting-started/connect-your-data.md) if you need help connecting a data source.
2. **Select a Data Source**: Use the dropdown menu to choose your data source. This action will display a list of available tables.
3. **Add Tables**: Click the **+ button** beside each table you want to include in your data product.

**Note**: You're limited to 5 tables per Data Product. For more extensive data sets, create multiple Data Products to ensure better performance and efficient querying by the Alkemi agent.

**Need Extra Tables?** Contact our team at <support@alkemi.ai> if you require additional tables.

<figure><img src="/files/4r44a0RNaoHWtKRioqXg" alt=""><figcaption></figcaption></figure>
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{% step %}

### Select Create Product

Once your new Data Product appears on the list, you can begin training it. This ensures Alkemi's agent efficiently answers complex questions by translating them into precise queries.
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---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.alkemi.ai/documentation/basics/data-products/creating-a-data-product.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.